Inteligencia artificial y comprensión lectora en estudiantes: una revisión sistemática
Artificial intelligence and Students' Reading Comprehension: A Systematic ReviewBarra lateral del artículo
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Contexto: La comprensión lectora constituye una competencia fundamental en el ámbito educativo, y su fortalecimiento se ha convertido en prioridad ante los desafíos que plantean las sociedades contemporáneas. En este contexto, la inteligencia artificial emerge como un recurso prometedor para intervenir en los procesos de lectura y comprensión de textos. Objetivo: El propósito de esta revisión sistemática fue analizar la producción científica sobre la relación entre la inteligencia artificial y la comprensión lectora en estudiantes, identificando las tecnologías empleadas, los efectos reportados y las percepciones de los actores educativos. Metodología: Se condujo una revisión sistemática siguiendo la declaración PRISMA 2020, con búsquedas en las bases de datos Scopus y Scielo, abarcando el periodo 2019-2025. Se aplicaron criterios de inclusión y exclusión definidos, y el análisis se realizó mediante síntesis narrativa y categorización temática. Resultados: Se incluyeron 50 estudios que evidenciaron un efecto predominantemente positivo de las herramientas de inteligencia artificial sobre la comprensión lectora, con énfasis en el aprendizaje personalizado, la retroalimentación adaptativa y el aumento de la motivación. También se identificaron preocupaciones éticas y dependencia tecnológica. Conclusión: La inteligencia artificial muestra potencial para fortalecer la comprensión lectora estudiantil, aunque se requieren investigaciones rigurosas que aborden sus implicaciones éticas y pedagógicas a largo plazo.
Background: Reading comprehension constitutes a fundamental competence in education, and its development has become a priority given the challenges of contemporary societies. In this context, artificial intelligence (AI) has emerged as a promising resource for enhancing reading and text comprehension processes. Objective: This systematic review analyzes the scientific production regarding the relationship between AI and student reading comprehension, identifying the technologies employed, reported effects, and the perceptions of educational stakeholders. Methods: A systematic review was conducted following PRISMA 2020 guidelines, with searches in Scopus and SciELO databases covering the 2019–2025 period. After applying inclusion and exclusion criteria, the analysis was performed through narrative synthesis and thematic categorization. Results: Fifty studies were included, demonstrating a predominantly positive effect of AI tools on reading comprehension, with emphasis on personalized learning, adaptive feedback, and increased motivation. Ethical concerns and technological dependence were also identified. Conclusion: AI shows significant potential to strengthen student reading comprehension, although rigorous research addressing its long-term ethical and pedagogical implications is required.
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